EAGER: Data Privacy for Smart Meter Data: A Scenario-Based Study
EAGER: Data Privacy for Smart Meter Data: A Scenario-Based Study
批准号:
1447589
负责人:
Jason Dedrick
金额:
$26.61万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2017-08-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Smart electric meters comprise one key technology element in an overall strategy to modernize the nation's energy infrastructure. Smart meters capture data on household energy usage at frequent intervals and transmit those data to utility companies, who use the data to automate meter reading and billing, detect and respond to outages, and manage grid operations. Data collected over time can be used to forecast demand, understand customer behavior and develop new service and pricing plans. In the long run, these data can drive forecasting and control models that allow utilities to respond rapidly to fluctuations in power demand with compensatory load control strategies. This capability can reduce the magnitude of peak demand, thereby reducing both infrastructure costs and the consumption of fossil fuels that power peak generation facilities. Despite these advantages, smart meter data also appear to create powerful customer privacy concerns that may inhibit the adoption of smart meter technology by utilities. To address privacy concerns pertaining to the smart meter data, this project proposes three studies: Study 1 uses public data on electricity usage to develop a set of privacy scenarios that will be tested in focus groups to explore consumer privacy concerns. Study 2 involves a quasi-experiment to assess key dimensions of the scenarios and help identify which scenario has the highest level of acceptability to consumers. Study 3 involves one-on-one discussions with utility company representatives to develop a toolbox of communication methods and content that balance consumers' privacy concerns with the goals and constraints of utilities. The current theoretical model of privacy and technology, based on an information boundary framework, posits that consumers' willingness to share private information is rooted in the nature of the relationship with the party with whom the information is shared. Although a number of researchers have applied this information boundary framework to intra-organizational situations, the framework has not been tested in the context of smart meter data privacy. In the proposed sequence of three studies, this project gathers data from informants with the intention of understanding whether the information boundary framework is applicable to examining the relationships between consumers and regulated monopolies. The proposed project provides insights into public attitudes and concerns, as well as industry practices and policies regarding privacy of smart meter data. Through direct interaction with utility companies, as well as dissemination at industry conferences, in trade journals and through the media, the researchers will share their findings with practitioners, regulators and others who can create solutions that give customers confidence about the protection of their data.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
SCC-Planning: Community Energy: Technical and Social Challenges and Integrative Solutions
-
批准号:1737550
-
项目类别:Standard Grant
-
资助金额:$10.0万
-
财政年份:2017
-
负责人:Jason Dedrick
-
依托单位:
SBE: Small: Cybersecurity risks of dynamic, two-way distributed electricity markets
-
批准号:1618803
-
项目类别:Standard Grant
-
资助金额:$34.42万
-
财政年份:2016
-
负责人:Jason Dedrick
-
依托单位:
Adoption of smart grid technologies by electrical utilities: Factors influencing organizational innovation in a regulated environment
-
批准号:1231192
-
项目类别:Standard Grant
-
资助金额:$33.32万
-
财政年份:2012
-
负责人:Jason Dedrick
-
依托单位:
国内基金
海外基金
登录
查看更多内容
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
-
批准号:--
-
项目类别:合作创新研究团队
-
资助金额:--
-
批准年份:2024
-
负责人:姚韬
-
依托单位:
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
-
批准号:--
-
项目类别:外国青年学者研究基金项目
-
资助金额:--
-
批准年份:2024
-
负责人:江洋子
-
依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
-
批准号:--
-
项目类别:--
-
资助金额:40万元
-
批准年份:2020
-
负责人:Vikrant Gupta
-
依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
-
批准号:61373035
-
项目类别:面上项目
-
资助金额:77.0万元
-
批准年份:2013
-
负责人:冯志勇
-
依托单位:
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
-
批准号:31070748
-
项目类别:面上项目
-
资助金额:34.0万元
-
批准年份:2010
-
负责人:Christine Nardini
-
依托单位:
高维数据的函数型数据(functional data)分析方法
-
批准号:11001084
-
项目类别:青年科学基金项目
-
资助金额:16.0万元
-
批准年份:2010
-
负责人:周迎春
-
依托单位:
染色体复制负调控因子datA在细胞周期中的作用
-
批准号:31060015
-
项目类别:地区科学基金项目
-
资助金额:25.0万元
-
批准年份:2010
-
负责人:莫日根
-
依托单位:
Computational Methods for Analyzing Toponome Data
-
批准号:60601030
-
项目类别:青年科学基金项目
-
资助金额:17.0万元
-
批准年份:2006
-
负责人:Axel Mosig
-
依托单位: